Systematic derivation of bounds and glue constraints for time-series constraints

Ekaterina Arafailova; Nicolas Beldiceanu; Mats Carlsson; Pierre Flener; María Andreína Francisco Rodríguez; Justin Pearson; Helmut Simonis

doi:10.1007/978-3-319-44953-1_2

Systematic derivation of bounds and glue constraints for time-series constraints

Ekaterina Arafailova
, Nicolas Beldiceanu
, Mats Carlsson
, Pierre Flener
, María Andreína Francisco Rodríguez
, Justin Pearson
, Helmut Simonis

IMT Atlantique
RISE Research Institutes of Sweden
Uppsala University

Research output: Chapter in Book/Report/Conference proceedings › Conference proceeding › peer-review

Abstract

Integer time series are often subject to constraints on the aggregation of the integer features of all occurrences of some pattern within the series. For example, the number of inflexions may be constrained, or the sum of the peak maxima, or the minimum of the peak widths. It is currently unknown how to maintain domain consistency efficiently on such constraints. We propose parametric ways of systematically deriving glue constraints, which are a particular kind of implied constraints, as well as aggregation bounds that can be added to the decomposition of time-series constraints [5]. We evaluate the beneficial propagation impact of the derived implied constraints and bounds, both alone and together.

Original language	English
Title of host publication	Principles and Practice of Constraint Programming - 22nd International Conference, CP 2016, Proceedings
Editors	Michel Rueher
Publisher	Springer Verlag
Pages	13-29
Number of pages	17
ISBN (Print)	9783319449524
DOIs	https://doi.org/10.1007/978-3-319-44953-1_2
Publication status	Published - 2016
Event	22nd International Conference on Principles and Practice of Constraint Programming, CP 2016 - Toulouse, France Duration: 5 Sep 2016 → 9 Sep 2016

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9892 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	22nd International Conference on Principles and Practice of Constraint Programming, CP 2016
Country/Territory	France
City	Toulouse
Period	5/09/16 → 9/09/16

Access to Document

10.1007/978-3-319-44953-1_2

Cite this

Arafailova, E., Beldiceanu, N., Carlsson, M., Flener, P., Francisco Rodríguez, M. A., Pearson, J., & Simonis, H. (2016). Systematic derivation of bounds and glue constraints for time-series constraints. In M. Rueher (Ed.), Principles and Practice of Constraint Programming - 22nd International Conference, CP 2016, Proceedings (pp. 13-29). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9892 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-44953-1_2

Arafailova, Ekaterina ; Beldiceanu, Nicolas ; Carlsson, Mats et al. / Systematic derivation of bounds and glue constraints for time-series constraints. Principles and Practice of Constraint Programming - 22nd International Conference, CP 2016, Proceedings. editor / Michel Rueher. Springer Verlag, 2016. pp. 13-29 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Systematic derivation of bounds and glue constraints for time-series constraints",

abstract = "Integer time series are often subject to constraints on the aggregation of the integer features of all occurrences of some pattern within the series. For example, the number of inflexions may be constrained, or the sum of the peak maxima, or the minimum of the peak widths. It is currently unknown how to maintain domain consistency efficiently on such constraints. We propose parametric ways of systematically deriving glue constraints, which are a particular kind of implied constraints, as well as aggregation bounds that can be added to the decomposition of time-series constraints [5]. We evaluate the beneficial propagation impact of the derived implied constraints and bounds, both alone and together.",

author = "Ekaterina Arafailova and Nicolas Beldiceanu and Mats Carlsson and Pierre Flener and \{Francisco Rodr{\'i}guez\}, \{Mar{\'i}a Andre{\'i}na\} and Justin Pearson and Helmut Simonis",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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Arafailova, E, Beldiceanu, N, Carlsson, M, Flener, P, Francisco Rodríguez, MA, Pearson, J & Simonis, H 2016, Systematic derivation of bounds and glue constraints for time-series constraints. in M Rueher (ed.), Principles and Practice of Constraint Programming - 22nd International Conference, CP 2016, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9892 LNCS, Springer Verlag, pp. 13-29, 22nd International Conference on Principles and Practice of Constraint Programming, CP 2016, Toulouse, France, 5/09/16. https://doi.org/10.1007/978-3-319-44953-1_2

Systematic derivation of bounds and glue constraints for time-series constraints. / Arafailova, Ekaterina; Beldiceanu, Nicolas; Carlsson, Mats et al.
Principles and Practice of Constraint Programming - 22nd International Conference, CP 2016, Proceedings. ed. / Michel Rueher. Springer Verlag, 2016. p. 13-29 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9892 LNCS).

Research output: Chapter in Book/Report/Conference proceedings › Conference proceeding › peer-review

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AU - Arafailova, Ekaterina

AU - Beldiceanu, Nicolas

AU - Carlsson, Mats

AU - Flener, Pierre

AU - Francisco Rodríguez, María Andreína

AU - Pearson, Justin

AU - Simonis, Helmut

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AB - Integer time series are often subject to constraints on the aggregation of the integer features of all occurrences of some pattern within the series. For example, the number of inflexions may be constrained, or the sum of the peak maxima, or the minimum of the peak widths. It is currently unknown how to maintain domain consistency efficiently on such constraints. We propose parametric ways of systematically deriving glue constraints, which are a particular kind of implied constraints, as well as aggregation bounds that can be added to the decomposition of time-series constraints [5]. We evaluate the beneficial propagation impact of the derived implied constraints and bounds, both alone and together.

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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Arafailova E, Beldiceanu N, Carlsson M, Flener P, Francisco Rodríguez MA, Pearson J et al. Systematic derivation of bounds and glue constraints for time-series constraints. In Rueher M, editor, Principles and Practice of Constraint Programming - 22nd International Conference, CP 2016, Proceedings. Springer Verlag. 2016. p. 13-29. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-44953-1_2

Systematic derivation of bounds and glue constraints for time-series constraints

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